Environment and Planning B: Urban Analytics and City Science

The agglomeration patterns of twenty-six manufacturing and service sectors in and around Paris in 1999 are analysed. The method used measures the intensity of spatial agglomeration and identifies the location patterns of economic sectors. First the locational Gini coefficient and Moran's I statistics of global spatial autocorrelation are computed. These provide different but complementary information about the spatial agglomeration of the sectors under study. Then exploratory spatial data analysis tools are applied. Moran scatterplots and local indicators of spatial association statistics reveal great diversity in location patterns across sectors.

From the point of view of a situated observer, the physical shape of buildings creates spatial relationships only some of which are present in perception while others are inherent in abstract descriptions of the objective structure of environment retrieved in the mind. In this paper the contributions of syntactic analysis to the study of the spatial structures involved in perception and cognition are illustrated through a study of Fallingwater at Bear Run, Laurel Highlands, PA. Fallingwater is chosen for its open layout, engendering quasi-synchronic visual fields bound by intricate wall shapes. Thus, it lends itself to a discussion of how spatial structures available to perception arise according to the arrangement of built shape and how they give rise to incrementally more abstract cognitive structures.

There is a paradoxical relationship between the density of solar housing and net household energy use. The amount of solar energy available per person decreases as density increases. At the same time, transportation energy, and to some extent, household operating energy decreases. Thus, an interesting question is posed: how does net energy use vary with housing density? This study attempts to provide insight into this question by examining three housing forms: low-density detached homes, medium-density townhouses, and high-density high-rise apartments in Toronto. The three major quantities of energy that are summed for each are building operational energy use, solar energy availability, and personal transportation energy use. Solar energy availability is determined on the basis of an effective annual collector efficiency. The results show that under the base case in which solar panels are applied to conventional homes, the high-density development uses one-third less energy than the low-density one. Improving the efficiency of the homes results in a similar trend. Only when the personal vehicle fleet or solar collectors are made to be extremely efficient does the trend reverse—the low-density development results in lower net energy.

Having a neighbourhood open space that is attractive and easy to visit can benefit older people's well-being. However, to date little research has explored the comparative importance of different attributes of local open space for older adults. This study drew on a sample of people from across Britain, aged from 60 to 97 years, to address this gap. It used choice-based conjoint analysis of environmental attributes relevant to older people's park preferences to demonstrate the comparative importance of nuisances such as signs of vandalism or dog fouling, and deterrents such as heavy traffic en route to an open space, as well as the importance of attractors such as cafes and toilets, trees and plants, things to watch, and good maintenance. The results published here provide the basis for scenario modelling to predict the effects of changes to any attribute in terms of overall preference. Key subgroups in the sample were identified, their responses differing significantly according to whether or not they lived alone or had any mobility impairment. The value of the research lies in demonstrating the effectiveness of the methods: scenario modelling can take these different subgroups' preferences into account and such analysis can be of considerable practical value to open-space planners and designers.

The research in this paper addresses human — environment interactions in Canadian cities by examining the spatial distribution of vegetation in relation to various socioeconomic indicators. Specifically, intercity and intracity comparisons are evaluated using correlation analysis and geographically weighted regression (GWR). Vegetation abundance estimates derived from spectral mixture analysis of Landsat imagery are compared with Canadian census data for the cities of Montreal, Toronto, and Vancouver to quantify vegetation-related environmental equity in Canada's largest urban centres. Results exhibit strong and consistent correlations between median family income and vegetation fraction for Montreal (r = 0.473), Toronto (r = 0.467), and Vancouver (r = 0.456). Furthermore, examining the GWR results suggests that employing an adaptive bandwidth kernel technique with a manual selection of ten neighbours for each observation provides a greater range and higher median values for local regression estimates (Montreal: 0.69; Toronto: 0.74; Vancouver: 0.73) as compared with the Akaike information criterion-selection method. Finally, we discuss the potential application of the presented analysis techniques for urban planning and community-development initiatives, specifically associated with managing vegetation-related environmental equity at various scales. Possible applications of these techniques for urban planning purposes are discussed, and key methodological considerations for performing such an analysis are highlighted.

Face-to-face social activities, such as joint activities with friends or visiting relatives, involve meeting with other persons at a certain time and location. This (social) spatial-choice behavior is critical for successful urban planning. Recently there has been a rapid emergence of research into social interactions in the field of urban planning and transport. This study contributes to our understanding of the relationships between face-to-face social interaction, location-type choice, and travel by presenting analyses based on social-contact diary data gathered for this study in a large-scale survey conducted in the Netherlands. The analysis framework consists of a set of linked linear regression and discrete choice models to predict the location-type choice for a given face-to-face social interaction, the distance to that location, and the transport mode. Furthermore, the model predicts outcomes of a chain of higher-level decisions including the number of face-to-face interactions and the purpose of the interaction. As independent variables, the model system includes sociodemographic and spatial variables. The results indicate that, to a moderate extent the number of face-to-face social interactions, the purpose of the interactions, and the travel distance can be explained by people's personal and residential variables. These variables have a strong impact on the type of location for the interaction and the transport mode used to get there.

The hidden orders of physical structure in Yuyuan, an example of Chinese gardens, are explored. Methods of geometric analysis are used to examine rules of iteration and transformation in the configuration model of the garden, for example, the spatial structure of ‘gardens in a garden’, the pedestrian system of ‘circles in a circle’, and the tree-like waterway, which formulate an irregular fractal system. It is argued that these generative rules of the structure, which mainly give rise to the similarities and complexities between parts and the whole garden, are deeply rooted in the principle of I Ching.

We present in this paper the development and application of a cellular automata model that uses irregular cells for simulating land-use change instead of the common regular cells based on the pixels of remote sensing images. The use of irregular cells combines urban form with reliable demographic, socioeconomic, and building data that are usually available for irregular census blocks. The calibration of the model is made through a procedure based on a particle swarm algorithm that optimises a measure of agreement derived from the kappa index for contingency matrices. The model was applied for simulating urban change in a small municipality in Portugal that registered high growth rates during the 1990s. Simulation results indicate the model's ability to capture land-use change in small urban areas.

The environmental crisis, the energy crisis, the financial crisis, and the subsequent economic crisis—to name only a few of the crucial issues of our times—are causing an outcry for change, even structural change, in our society. Change is the sum of a great number of acts (individual, group, institutional) of reperception and behaviour change at every level. This takes decision makers, planners, institutions, and citizens out of their comfort zones and compels them to confront their key beliefs, to challenge conventional wisdom, and to examine the prospects of ‘breaking out of the box’. Not everyone (individual planners, groups, institutions, citizens) wants to give up the power associated with the status quo. Society is starting to reflect on new concepts and new ways of thinking that change the way resources are used, (re)distributed, and allocated, and the way the regulatory powers (market versus state) are exercised. As the call for change has been central to planning, one of the key challenges is to develop an approach to planning that will make these ideas and concepts ‘travel’ and that will translate them into an array of practice arenas, which in turn will transform these arenas themselves, rather than merely being absorbed within them. The spectrum for change cannot be so open that anything is possible, as if we could achieve anything we wanted to achieve. Conditions and structural constraints on ‘what is’ and ‘what is not’ possible are imposed by the past and the present. These conditions and constraints have to be questioned and challenged in the process, given the specific context of time and place. So, in order to imagine the conditions and constraints differently, we need to deal with history and to overcome history. This defines the boundaries of a fairly large space between openness and fixity. Thus, change becomes the activity whereby (within certain boundaries) that which might become is ‘imposed’ on that which is, and it is ‘imposed’ for the purpose of transforming what ‘is’ into what ‘might become’. This differs from the established or traditional way of thinking, in which there is no choice and we are not even aware of other possibilities. In this paper I argue for a strategic planning approach that focuses, invents, creates, and is implemented—in relation to the context, and to the social and cultural values to which a particular place or society is historically committed—as something new rather than as a solution arrived at as a result of existing trends. It is only by working backwards (‘reverse thinking’, ‘back casting’) that planning is able to open up new perspectives and take other directions. Subsequently I reflect on the changing role of planners in this respect.

In this paper the design and execution of a simple AutoLISP routine for generating a map of plan isovists (in the sense of Benedikt) are discussed. Such a plan field of isovists is a registration of visibility from multiple station points within and around a building. More precisely, the plan field records the cumulative effect, over a spatial matrix, of occluded vision of a distant horizon. Thus, the plan field is termed an occlusion map. An occlusion map registers the effect which an observer's position in space has on their perception of architecture's visual permeability. Occlusion maps are shown here to be an important tool for comparing existing buildings in a historical sense and also as an effective design tool, particularly when an addition to an existing building is being contemplated, as an addition invariably affects the visual permeability of its host.